ORCA: Oceanic Recognition & Classification Application for sea-life analysis systems.

This project is a collaborative fog node-based fish detection system. It leverages fog computing to distribute image processing tasks across multiple clients and a server. The system is designed to detect fish in images and provide bounding box information using the Roboflow API.

This project is a collaborative fog node-based fish detection system. It leverages fog computing to distribute image processing tasks across multiple clients and a server. The system is designed to detect fish in images and provide bounding box information using the Roboflow API.

Fish Identifier App using Flutter

This code is a PyTorch implementation of ClassAwareLoss proposed in the "Class-aware fish species recognition using deep learning for an imbalanced dataset" paper. https://www.mdpi.com/1424-8220/22/21/8268

AutoFiS: Automatic Identification of Fish Species

This repository contains the code used to create the results and figures in our Machine learning based region of interest detection in airborne lidar fisheries surveys paper, which was published in the SPIE Journal of Applied Remote Sensing.

Fish detection using Open Images Dataset and Tensorflow Object Detection

Fish detector using Deep learning - ResNet Model with ImageNet weights

물고기 인식 어플

Fish instance segmentation using Mask-RCNN